Method and system for detecting a fallen person using a range imaging device

ABSTRACT

A method and system for detecting a fallen person is described. An initial range image corresponding to a field of view of a DAS is generated. Further, a reference plane disposed in the field of view is identified. Additionally, one or more regions in the initial range image indicative of one or more objects disposed above the reference plane in the field of view are determined. Further, the DAS regenerates a range image corresponding to the field of view after a determined time period. The regenerated range image is compared with the initial range image to determine if the regenerated range image comprises a new object disposed above the reference plane. The new object is determined to be the fallen person if a height of the new object is less than a determined height and a volume and/or a surface area of the new object is greater than a determined value.

BACKGROUND

Embodiments of the present technique relate generally to healthmonitoring, and more particularly to methods and systems for falldetection.

Unintentional falls are one of the most complex and costly health issuesfacing elderly people. Recent studies show that approximately one inevery three adults age 65 years or older falls each year, and about 30percent of these falls result in serious injuries. Particularly, peoplewho experience a fall event at home may remain on the ground for anextended period of time as help may not be immediately available. Thestudies indicate a high mortality rate amongst such people who remain onthe ground for an hour or more after a fall.

Fall detection (FD), therefore, has become a major focus of healthcarefacilities. Conventionally, healthcare facilities employ nursing staffto monitor a person around the clock. In settings such as assistedliving or independent community life, however, the desire for privacyand the associated expense render such constant monitoring undesirable.Accordingly, FD systems based on wearable devices including sensors suchas accelerometers, gyroscopes and/or microphones have been proposed.These devices, however, may need to be activated by a fallen personusing a push-button to alert appropriate personnel or a healthmonitoring system. FD systems based on such wearable devices, therefore,may be successful only if the person wears the sensing devices at alltimes and is physically and cognitively able to activate the alarm whenan emergency arises.

Therefore, in recent times, video-based FD systems are being widelyinvestigated for efficient fall detection. Conventional video-based FDsystems process images of the person's motion in real time to evaluateif detected horizontal and vertical velocities corresponding to theperson's motion indicate a fall event. Determination of the horizontaland vertical velocities while detecting human falls involves use ofcomplex computations and classification algorithms, thereby requiring agreat deal of processing power and expensive equipment. Additionally,such video-based FD systems fail to robustly detect slow falls that maybe characterized by low horizontal and vertical velocities. Further, useof such video-based FD systems typically involves acquisition ofpersonally identifiable information leading to numerous privacyconcerns. Specifically, constant monitoring and acquisition ofidentifiable videos is considered by many people to be an intrusion oftheir privacy.

It may therefore be desirable to develop an effective method and systemfor detecting high-risk movements, especially human fall events.Specifically, there is a need for a relatively inexpensive FD systemcapable of easily and accurately computing one or more parametersindicative of potential fall events such as a size and a distancecorresponding to objects disposed in an FD environment. Additionally,there is a need for an FD method and a system that non-intrusively yetreliably detect a wide variety of falls with a fairly low instance offalse alarms.

BRIEF DESCRIPTION

In accordance with aspects of the present technique, a method fordetecting a fallen person is presented. The method includes generatingan initial range image corresponding to a field of view of a dataacquisition system. Particularly, a reference plane disposed in thefield of view of the data acquisition system is identified.Additionally, one or more regions in the initial range image indicativeof one or more objects disposed above the reference plane in the fieldof view of the data acquisition system are determined. Further, the dataacquisition system regenerates a range image corresponding to the fieldof view of the data acquisition system after a determined time period.The regenerated range image is then compared with the initial rangeimage to determine if the regenerated range image comprises a new objectdisposed above the reference plane. Subsequently, the new objectdisposed above the reference plane is determined to be the fallen personif a height of the new object is less than a determined height and atleast one of a volume and a surface area of the new object is greaterthan a determined value.

In accordance with aspects of the present system, a system for detectinga fallen person is described. To that end, the fall detection systemincludes a data acquisition system that generates an initial range imagecorresponding to a field of view of the data acquisition system. Thefall detection system further includes a processing subsystemcommunicatively coupled to the data acquisition system. The processingsubsystem identifies a reference plane disposed in the field of view ofthe data acquisition system. Further, the processing subsystemdetermines one or more regions in the initial range image indicative ofone or more objects disposed above the reference plane in the field ofview of the data acquisition system. Additionally, the processingsubsystem regenerates a range image corresponding to the field of viewof the data acquisition system after a determined time period. Theprocessing subsystem then compares the regenerated range image with theinitial range image to determine if the regenerated range imagecomprises a new object disposed above the reference plane. Subsequently,the processing subsystem determines whether the new object disposedabove the reference plane is the fallen person if a height of the newobject is less than a determined height and at least one of a volume anda surface area of the new object is greater than a determined value.

DRAWINGS

These and other features, aspects, and advantages of the presenttechnique will become better understood when the following detaileddescription is read with reference to the accompanying drawings in whichlike characters represent like parts throughout the drawings, wherein:

FIG. 1 is a block diagram of an exemplary system for detecting a fallenperson, in accordance with aspects of the present system;

FIG. 2 is a block diagram of the system for detecting the fallen personillustrated in FIG. 1, in accordance with aspects of the present system;

FIG. 3 is a flow chart illustrating an exemplary method for detecting afallen person, in accordance with aspects of the present technique;

FIG. 4 is an illustration of an exemplary range image generated by an FDsystem, in accordance with aspects of the present technique; and

FIG. 5 is an illustration of another exemplary range image generated byan FD system, in accordance with aspects of the present technique.

DETAILED DESCRIPTION

The following description presents systems and methods for monitoring aperson. Particularly, certain embodiments illustrated herein describesystems and methods for detecting a fallen person using a 3-dimensional(3D) depth camera or a 3D range camera. In the following description,the terms ‘3D depth camera’ and ‘3D range camera’ are usedinterchangeably for referring to a device that captures a depth value ora range value of a pixel in a scene. Moreover, the terms ‘depth value’or ‘range value’ refer to a relative distance of the pixel from areference point such as the 3D range camera. Although the present systemdescribes the use of a 3D range camera, the system may include any othersuitable type of range imaging device, such as an active infrared and/ora time-of-flight (TOF) device, for use in different operatingenvironments for detecting a fallen object. An exemplary environmentthat is suitable for practicing various implementations of the presentsystem is described in the following sections with reference to FIG. 1.

FIG. 1 illustrates an exemplary system 100 for monitoring an object suchas a fallen person 102, a kneeling person 103, and so on. In oneembodiment, the system 100 includes a data acquisition system (DAS) 104for monitoring a field of view 106 and one or more objects that may bedisposed in the field of view 106 of the DAS 104. By way of example, thefield of view 106 may include a room including one or more objects suchas the fallen person 102, the kneeling person 103, furniture 108 such asbed, chair, and table or other room structures such as columns andchandeliers (not shown). In accordance with aspects of the presenttechnique, the DAS 104 generates an initial range image of the field ofview 106 based on a distance of the one or more objects 102, 103, 108disposed in the field of view 106 from a reference point. By way ofexample, the reference point may include the DAS 104, a reference planeor any other suitable reference element disposed in the field of view106. Specifically, the DAS 104 generates the initial range image of thefield of view 106 based on a relative distance of a plurality of pixelscorresponding to the field of view 106 and/or the one or more objects102, 103, 108 disposed in the field of view 106 from the referencepoint. To that end, the DAS 104 may include any suitable type of rangeimaging device operating on, for example, TOF, coded aperture,structured light, or triangulation principles. Further, in accordancewith aspects of the present technique, the DAS 104 does not processidentifiable video images, and therefore is less invasive on personalprivacy.

In certain embodiments, the DAS 104 may include optics 105 such as awide-angle lens for capturing large areas of the field of view 106reliably and cost effectively. Alternatively, the DAS 104 mayspecifically monitor relevant regions of the field of view 106 where arisk associated with a potential fall event may be high. The DAS 104,therefore, is appropriately positioned at a desired position toeffectively monitor the relevant regions of the field of view 106.Accordingly, in one embodiment, the DAS 104 is approximately positionedat the center of the ceiling of the room for monitoring the field ofview 106 and the one or more objects 102, 103, 108 disposed in the fieldof view 106. Positioning the DAS 104 at the center of the ceiling mayminimize the area that may be shielded from view by the furniture 108.In alternative embodiments, however, the DAS 104 may be positioned atother locations such as on one of the walls adjacent to a staircase or astair well that allow for the field of view 106 of the DAS 104 toinclude regions where a risk associated with a potential fall event maybe high.

Although the presently illustrated embodiment in FIG. 1 depicts a singleDAS 104, multiple DASs may be disposed at different locations in theroom for effectively monitoring a wide area such as a large room or aroom with structures or objects that impair the field of view.Particularly, in certain embodiments, the multiple DASs may operateindependently or be communicatively coupled through wired and/orwireless links to each other and/or a central health monitoring systemfor communicating alerts and other information regarding potential fallevents detected in the field of view 106.

Further, in accordance with aspects of the present technique, the DAS104 generates an initial range image corresponding to the field of view106 and the one or more objects disposed in the field of view 106.Particularly, the DAS 104 generates the initial range image based on arange or a depth value corresponding to the plurality of pixelscorresponding to the one or more objects disposed in the field of view106. As previously noted, the range or depth value corresponds to arelative distance of the plurality of pixels corresponding to the one ormore objects disposed in the field of view 106 from the reference point.

Accordingly, in one embodiment, the DAS 104 includes a 3D range camerabased on the TOF principle. Further, the DAS 104 captures the rangevalue or the depth value corresponding to an object such as the fallenperson 102 disposed in the field of view 106. To that end, in certainembodiments, the DAS 104 emits pulses of infra-red (IR) light towardsthe one or more objects and detects the light reflected from a surfaceof the one or more objects. The energy corresponding to the lightreflected from the one or more objects 102, 103, 108 disposed in thefield of view 106 correlates inversely to the relative distances of theone or more objects disposed in the field of view 106.

In one embodiment, the DAS 104 uses the inverse correlation between thedetected energy and relative distances of the one or more objectsdisposed in the field of view 106 to generate the initial range image asa depth map corresponding to the field of view 106. Alternatively, ifthe DAS 104 is positioned on a sidewall in the room, standardtrigonometric functions may be used to appropriately modify the distancecalculations for determining the relative distances of the one or moreobjects disposed in the field of view 106. Further, the DAS 104 mayrepresent the range or depth value corresponding to each of the one ormore objects disposed in the field of view 106 in the initial rangeimage using, for example, a plurality of grey scale values.Particularly, each grey-scale value corresponds to a relative distanceof the plurality of pixels corresponding to the one or more objectsdisposed in the field of view 106. Alternatively, the range or depthvalue may be represented using a colored scale with each colorindicative of a determined distance of the plurality of pixelscorresponding to the one or more objects disposed in the field of view106. Additionally, the one or more objects disposed in the field of view106 are arranged in layers in the initial range image according to thedetermined distance of the corresponding plurality of pixels from thereference point. The initial range image, thus, provides the depthinformation corresponding to the one or more objects disposed in thefield of view 106 in near real time while using minimal processingpower.

To that end, the system 100 identifies a reference plane 110 in theinitial range image corresponding to the field of view 106 fordetermining the relative positioning of the one or more objects disposedin the field of view 106. By way of example, the reference plane 110corresponds to the floor of a room, a bed disposed in the room, or anyother suitable plane in the field of view 106. In one embodiment, agroup of pixels oriented as a plane disposed furthest from the DAS 104on an axis substantially perpendicular to the DAS 104 is identified asthe reference plane 110. In an alternative embodiment, an exemplaryheuristic selects the largest cluster disposed at the furthest distancefrom the DAS 104 as the reference plane 110.

Alternatively, a group of pixels oriented as a plane having the lowest Zcoordinate position in the field of view 106 may be identified as thereference plane 110. In certain other embodiments, a plane at adetermined distance from the DAS 104 may be designated to be thereference plane 110. To that end, the system may include, for example, aswitching mechanism to select a mounting height of the DAS 104 to be setat a designated height such as 8, 10, or 12 feet from the referenceplane such as a floor in a room. Additionally, in embodiments where theDAS 104 is mounted on a sidewall adjacent to a staircase or stair well,the reference plane 110 may be derived to generate a relative referenceplane, an angled reference plane, or a plurality of reference planessuch as in relation to a number of stairs.

Accordingly, in certain embodiments, the DAS 104 may include a processorand a memory (not shown) for identifying the reference plane 110 andperforming related computations. Alternatively, the DAS 104 may beoperatively coupled to a processing subsystem 112 through wired and/orwireless network connections (not shown) for determining the referenceplane 110 and performing the related distance computations. By way ofexample, the DAS 104 may be coupled to the processing subsystem 112through a wireless transceiver or a transmitter (not shown) forcommunicating all or portions of acquired image data to the processingsubsystem 112. Further, the processing subsystem 112 may include one ormore microprocessors, microcomputers, microcontrollers, and so forth,for processing the acquired image data. The processing subsystem 112, insome embodiments, may further include memory (not shown) such as RAM,ROM, disc drive or flash memory. Particularly, the processing subsystem112 may use the memory for storing range values associated with thepixels corresponding to the field of view 106, positional coordinates ofthe reference plane 110 in the field of view 106, and so on.

Further, the processing subsystem 112 determines one or more regions inthe initial range image to be representative of the one or more objectsdisposed in the field of view 106. Particularly, the processingsubsystem 112 identifies one or more surfaces disposed above thereference plane 110 in the initial range image to be representative ofthe one or more objects disposed in the field of view. Alternatively,the one or more surfaces may be identified using the range imagecorresponding to the field of view 106.

The one or more surfaces, thus determined, are indicative ofdiscontinuities in the reference plane 110, and therefore may berepresentative of the one or more objects such as the furniture 108 orroom structures disposed in the field of view 106. The processingsubsystem 112 further stores information relating to the reference plane110 and the one or more objects disposed above the reference plane 110in the initial range image as baseline information corresponding to thefield of view 106. The baseline information determined from the initialrange image may be indicative of a default configuration of the one ormore objects disposed in the field of view 106, such as a room.

Additionally, in certain embodiments, the processing subsystem 112 masksthe one or more objects identified from the initial range image as beingrepresentative of safe regions. Generally, the safe regions correspondto the regions of the field of view 106 where a risk associated with apotential fall event is low. The safe regions, thus, can beautomatically determined based on the initial range image. Otherembodiments, however, may allow processing subsystem 112 to determinethe safe regions semi-automatically based on user input, or manually bya user. By way of example, the user can employ a graphical userinterface (GUI) display of the room to select the safe regions bydenoting them via the GUI.

Further, the processing subsystem 112 can direct the DAS 104 toregenerate a range image corresponding to the field of view 106 after adetermined time period. In certain embodiments, the DAS 104 continuallyregenerates the range image corresponding to the field of view 106 afterthe determined time period while monitoring the field of view 106 fornew objects. By way of example, the determined time period maycorrespond to about 1/10th of a second. Alternatively, the determinedtime period may be based on user preferences and/or applicationrequirements to ensure early detection of new objects in the field ofview 106.

Subsequently, the processing subsystem 112 compares the regeneratedrange image with the initial range image for determining if theregenerated range image includes a new object disposed in the field ofview 106. Specifically, the processing subsystem 112 determines if theregenerated range image includes a new surface disposed above thereference plane 110 in addition to the masked objects identified in theinitial range image. It may be noted that the new surface may correspondto a cluster of pixels disposed above the reference plane 110 in thefield of view 106. Upon identifying the new surface, the processingsubsystem 112 designates the new surface to be representative of the newobject disposed above the reference plane 110. Further, the processingsubsystem 112 determines a relative distance of the new object disposedabove the reference plane 110. Additionally, the processing subsystem112 determines a height, a surface area and/or a volume of the newobject to determine if the new object corresponds to the fallen person102 or a person disposed in a low-risk position such as the person 103in a kneeling or a standing position.

In one embodiment, the height of the new object is determined based on adistance of the highest pixel corresponding to the new object from thereference plane 110. Moreover, the surface area and the volume of thenew object may be determined by computing the surface area and thevolume of each of the pixels corresponding to the new object. By way ofexample, the processing subsystem 112 may apply standard trigonometricfunctions to range values associated with each of the pixelscorresponding to the new object for determining an approximate size ofeach corresponding pixel. As previously noted, the range valuesassociated with each of the pixels correspond to a relative distance ofeach of the pixels from the reference point. Further, a sum of theapproximate size of each of the pixels corresponding to the new objectis indicative of the surface area of the new object.

Similarly, the processing subsystem 112 may determine a volume of eachof the pixels corresponding to the new object based on a product of anapproximate size and a determined height of each of the pixels above thereference plane 110. The processing subsystem 112 may then determine avolume of the new object based on a sum of the individual volumes ofeach of the pixels corresponding to the new object. In one embodiment,the processing subsystem 112 may use the volume of the new object tosimply screen out unimportant objects and/or pets that may have movedinto the field of view 106 without having to evaluate their shapes. Incertain embodiments, however, the processing subsystem 112 may use adetermined size and/or shape of an object to perform more complexmasking of unimportant objects and/or pets while generating the initialrange image, thereby minimizing false alarms.

Further, in accordance with aspects of the present technique, theprocessing subsystem 112 determines if the height corresponding to thenew object is less that a determined height 114 and the surface areaand/or the volume corresponding to the new object is greater than adetermined value of surface area and/or volume. In one embodiment, thedetermined height 114 corresponds to a height such that a substantialportion of high-risk movements such as the person 102 crawling into theroom or twitching on the floor may be confined below the determinedheight 114. In another embodiment, the determined height 114 correspondsto a waist height of the person 102, such as about 21 inches above thereference plane 110.

Generally, the processing subsystem 112 designates a height as thedetermined height 114 so as to minimize false alarms. Specifically, theprocessing subsystem 112 designates the height to ensure that at least aportion of the low-risk movements corresponding to a person lying on thebed (not shown), or the person 103 in the kneeling position, or sittingin a chair (not shown) is detected above the determined height 114.Similarly, the processing subsystem 112 designates a surface area, forexample about 3 ft², corresponding to a surface area of an averageperson disposed in a low-risk position such as while standing or sittingin the field of view 106 as the determined surface area. Typically, asurface area greater than the determined surface area is indicative ofthe person 102 who may have fallen and is disposed on the floor.

Additionally, the processing subsystem 112 may designate a volume, forexample about 18,000 cm³, corresponding to the kneeling person 103disposed in low-risk positions as the determined volume. Particularly, avolume greater than the determined volume may be indicative of theperson 102 who may have fallen and is disposed on the floor. In certaincases, however, such as when the kneeling person 103 stands withoutstretched arms and a volume computation includes volume of the pixelscorresponding to the top of the arm to the reference plane 110, thevolume of the person 103 may be greater than the determined volume. Inorder to prevent false alarms in such cases, the processing subsystem112 further verifies if the height of the new object is less than thedetermined height 114. The processing subsystem 112, however, may stilluse the volume computation to distinguish a person from a cat, a dog orother small objects.

Thus, the processing subsystem 112 designates the new object to be thefallen person 102 if the height of the new object is less than thedetermined height 114 and the surface area and/or the volume of the newobject is greater than the determined surface area and/or the determinedvolume, respectively. In one embodiment, the processing subsystem 112designates the new object to be the fallen person 102 if the valuescorresponding to the height, the surface area and/or the volume of thenew object do not substantially change over a determined period of time.Further, the processing subsystem 112 may determine a crawling movementof the person 102 based on movement of corresponding pixels indicated bythe regenerated range image. Accordingly, one or more settings of theprocessing subsystem 112 may be customized to designate the person 102determined to be crawling for more than the determined period of time tobe a fallen object.

In embodiments relating to human fall detection, the determined periodof time corresponds to a recovery time during which the person 102 mayget up subsequent to a fall, and therefore, the height of the person 102exceeds the determined height. By way of example, the determined periodof time may be about 90 seconds. The processing subsystem 112, however,may vary the determined period of time based on other parameters such asa location of the fall and/or the presence of another person in thefield of view 106.

Further, if the height of the new object is less than the determinedheight 114 and a surface area and/or the volume of the new object isgreater than the determined surface area and/or the determined volume,the processing subsystem 112 generates an output. Specifically, theprocessing subsystem 112 generates the output through an output device116 coupled to the DAS 104 and/or the processing subsystem 112.Moreover, the generated output includes an audio output and/or a visualoutput such as flashing lights, display messages and/or an alarm. Tothat end, the output device 116 includes an alarm unit, an audiotransmitter, a video transmitter, a display unit, or combinationsthereof, to generate the audio output and/or the video output.Additionally, the output device 116 generates and/or communicates analert output signal through a wired and/or wireless link to appropriatepersonnel and/or another monitoring system to generate a warning orperform any other specified action. By way of example, the specifiedaction may include sounding an alarm, sending an alert message to amobile device such as a voice message, text message or email, flashinglights coupled to the system 100, and so on.

Thus, unlike conventional monitoring applications where determining fallevents require complicated computations and expensive equipment, theprocessing subsystem 112 employs simple yet robust computations fordetecting fall events. Specifically, the processing subsystem 112detects a variety of fall events such as a slip fall, a slow fall and/orvarious other motion events simply by determining the height, thesurface area and/or the volume of the new object disposed above thereference plane 110 in the field of view 106 over the determined timeperiod. The determination of the height, the surface area and/or thevolume of the new object is greatly facilitated by the use of a 3D rangecamera as the DAS 104 in the present embodiment.

Moreover, the 3D range camera uses a depth map of the field of view 106as opposed to using an entire image to detect the fallen person 102 usedin conventional video-based FD applications. As previously noted, thedepth map includes a plurality of range values representative of arelative distance of each pixel corresponding to the person 102 ratherthan a personally identifiable image and/or video of the person 102.Employing the depth map, thus, eliminates the need to store imagesand/or other personally identifiable information, thereby mitigatingprivacy concerns.

Further, the 3D range camera generates a range image of the entire fieldof view 106 simultaneously as opposed to reading one pixel or line at atime as in conventional FD applications. The use of the 3D range cameraas the DAS 104, thus, enables faster computations while using minimalprocessing. The structure and functioning of a system for monitoring anobject using a 3D range camera, in accordance with aspects of thepresent technique, will be described in greater detail with reference toFIGS. 2-3.

FIG. 2 illustrates an exemplary block diagram of a system 200 formonitoring an object such as the person 102 of FIG. 1. For clarity, thesystem 200 is described with reference to the elements of FIG. 1. In oneembodiment, the system 200 includes the DAS 104 operatively coupled tothe processing subsystem 112 of FIG. 1 through a communication network202. By way of example, the communication network 202 includes wirednetworks such as LAN and cable, and/or wireless networks such as WLAN,cellular networks, satellite networks, and short-range networks such asZigBee wireless sensor networks. Further, the communication network 202facilitates transmission of data captured by the DAS 104 to theprocessing subsystem 112 while monitoring a field of view, such as thefield of view 106 of FIG. 1.

To that end, the DAS 104 is positioned at a desired position, such asapproximately at the center of the ceiling in the field of view 106 toeffectively monitor large areas of the field of view 106. Alternatively,the DAS 104 may be positioned at other locations such as on a walladjacent to a staircase to monitor specific areas of the field of view106 where a risk associated with a fall event is high. Onceappropriately positioned, the DAS 104 generates an initial range imageof the field of view 106. Particularly, the DAS 104 generates theinitial range image based on range values associated with the pixelscorresponding to the field of view 106. As previously noted, each of therange values corresponds to a relative distance of the pixel or eachgroup of pixels corresponding to the field of view 106 and/or the one ormore objects disposed in the field of view 106. Particularly, the rangevalues corresponds to relative distances of the one or more objects froma reference plane such as the reference plane 110 of FIG. 1, the DAS 104or another reference point disposed in the field of view 106.

Accordingly, in one embodiment, the DAS 104 includes an image sensorarray 204 for capturing the pixels corresponding to the field of view106 and a range sensor array 206 for determining a range valueassociated with each of the pixels. Further, in certain embodiments, theDAS 104 may also include a radiation source 208 and a detector array210. The radiation source 208 illuminates the field of view 106, whereasthe detector array 210 detects an intensity of radiation reflected fromone or more objects disposed in the field of view 106. By way ofexample, the radiation source 208 may include a laser or other suitabletype of light source, whereas the detector array 210 may include aCharge-Couple Device (CCD) or Complementary Metal-Oxide-Semiconductor(CMOS). Additionally, the DAS 104 may include a modulator 212 formodulating the radiation source 208 such that the radiation source 208emits one or more short pulses of radiation towards the field of view106 at desired time intervals, for example, every ten seconds.

In one embodiment, the range sensor array 206 determines a distance ofpixels corresponding to one or more objects disposed in the field ofview 106 from the DAS 104. Specifically, the range sensor array 206determines the distance based on a time taken by the short pulses totravel from the radiation source 208 to the one or more objects and backto the detector array 210. To that end, the processing subsystem 112includes timing circuitry 214 operatively coupled to the range sensorarray 206 for determining the travelling time of the short pulses.Moreover, the energy detected by the detector array 210 for the pixelscorresponding to the field of view 106 and the one or more objectsdisposed in the field of view 106 varies inversely with a distance ofthe pixels from the DAS 104. The range sensor array 206, therefore,determines the distance of the one or more objects from the DAS 104based on detected energy of the corresponding pixels, the determinedtravelling time of the pulses and the knowledge of the speed of light.In alternative embodiments, where the DAS 104 is positioned on a wall ofthe room, standard trigonometric functions may be used to appropriatelymodify the distance computations. Particularly, the distancecomputations may be modified for reconciling an angular positioning ofthe DAS 104 and/or calculating relative distances from another referencepoint such as the reference plane 110.

Subsequently, the DAS 104 correlates image data captured by the imagesensor array 204 with range data determined by the range sensor array206 for the pixels corresponding to the field of view 106. To that end,in certain embodiments, the processing subsystem 112 includes a memory216 for storing the image data, the range data, and correlations therebetween, for the pixels corresponding to the field of view 106.Specifically, in one embodiment, the DAS 104 uses the storedcorrelations to generate an initial 3D range image of the field of view106 and the one or more objects disposed in the field of view 106. Aspreviously noted, the initial range image provides a baselineconfiguration of the field of view 106 and the one or more objectsdisposed in the field of view 106. Further, the DAS 104 communicates theinitial range image to the processing subsystem 112.

In accordance with aspects of the present technique, the processingsubsystem 112 identifies a group of pixels oriented as a plane havingthe lowest Z coordinate position in the initial range image as thereference plane 110. As previously noted, the reference plane 110 mayinclude a floor of a room, a bed or chair disposed in the room, or anyother suitable plane in the field of view 106. The processing subsystem112 further determines one or more regions in the initial range imageindicative of one or more surfaces disposed above the reference plane110. Particularly, the processing subsystem 112 determines the one ormore regions to be representative of one or more objects disposed abovethe reference plane 110 in the field of view 106. Moreover, in certainembodiments, the processing subsystem 112 masks the one or more objectsidentified from the initial range image as being representative of saferegions where a risk associated with a potential fall event is low.

Further, the processing subsystem 112 directs the DAS 104 to continuallyregenerate a range image corresponding to the field of view 106 aftereach determined time period. Subsequently, the processing subsystem 112compares the regenerated range image with the initial range image fordetermining if the regenerated range image includes a new objectdisposed in the field of view 106. Specifically, the processingsubsystem 112 determines if the regenerated range image includes a newsurface disposed above the reference plane 110 in addition to the maskedobjects identified in the initial range image. Upon identifying the newsurface, the processing subsystem 112 designates the new surface to berepresentative of the new object disposed above the reference plane 110.

Subsequently, the processing subsystem 112 determines a height and asurface area and/or a volume of the new object. As previously noted, theheight of the new object may be determined based on a distance of thehighest pixel of the new object from the reference plane 110. Further,the surface area of the new object may be determined by summing anapproximate size of each of the pixels corresponding to the new objectdetermined by applying standard trigonometric functions to range valuesassociated with the corresponding pixels. Moreover, the maximum volumeof the new object may be determined by summing the volume of space abovethe reference plane 110 represented by each individual pixelcorresponding to the new object.

Further, in accordance with aspects of the present technique, theprocessing subsystem 112 determines if the height of the new object isless that the determined height 114 and the surface area and/or thevolume of the new object is greater than a determined surface areaand/or a determined volume, respectively. In one embodiment, thedetermined height 114 corresponds to a waist height of the person 102,such as about 21 inches above the reference plane 110. Moreover, thedetermined surface area corresponds to a surface area, such as about 3ft², of an average person disposed in a low-risk position such as whilestanding or sitting in the field of view 106. Similarly, the determinedvolume may correspond to a volume, such as 18,000 cm³, of a persondisposed in a low-risk position. Therefore, the processing subsystem 112designates the new object to be the fallen person 102 if the height ofthe new object is less than the determined height 114 and a surface areaand/or the volume of the new object is greater than the determinedsurface area and/or the determined volume, respectively.

Specifically, the processing subsystem 112 designates the new object tobe the fallen person 102 if the values corresponding to the height andthe surface area and/or the volume of the new object do notsubstantially change over a determined period of time, such as about 90seconds. As previously noted, the determined period of time correspondsto a recovery time during which the fallen person 102 may get upsubsequent to a fall. Such a comparison of the height, the surface areaand/or the volume of the new object with the determined height, thedetermined surface area and/or the determined volume prevents smallobjects such as pets and moving furniture from triggering an alert,thereby avoiding numerous false alarms. Certain embodiments, however,may allow the system 200 to be reset to a default position in case of afalse alarm.

Further, the processing subsystem 112 generates an output if the heightof the new object is less than the determined height 114 and a surfacearea and/or the volume of the new object is greater than the determinedsurface area and/or the determined volume, respectively. As previouslynoted, an object disposed at a height less than the determined height114 in the field of view 106 and having a surface area and/or a volumegreater than the determined surface area and/or the determined volume isindicative of the person 102 having experienced a potential fall event.Therefore, upon determining that the person 102 may have experienced apotential fall event, the processing subsystem 112 communicates thegenerated output to appropriate personnel or a healthcare monitoringsystem. Thus, in some embodiments, the system 200 may be implemented asa standalone system for monitoring an object in a field of view. Inalternative embodiments, however, the system 200 may be implemented aspart of a larger healthcare system for detecting the person 102 who mayhave experienced a fall event.

Turning to FIG. 3, a flow chart 300 depicting an exemplary method formonitoring an object in a field of view is presented. The exemplarymethod may be described in a general context of computer executableinstructions on a computing system or a processor. Generally, computerexecutable instructions may include routines, programs, objects,components, data structures, procedures, modules, functions, and thelike that perform particular functions or implement particular abstractdata types. The exemplary method may also be practiced in a distributedcomputing environment where optimization functions are performed byremote processing devices that are linked through a communicationnetwork. In the distributed computing environment, the computerexecutable instructions may be located in both local and remote computerstorage media, including memory storage devices.

Further, in FIG. 3, the exemplary method is illustrated as a collectionof blocks in a logical flow chart, which represents a sequence ofoperations that may be implemented in hardware, software, orcombinations thereof. The various operations are depicted in the blocksto illustrate the functions that are performed generally duringgeneration of a range image, detection of a fallen object, and otherphases of the exemplary method. In the context of software, the blocksrepresent computer instructions that, when executed by one or moreprocessing subsystems, perform the recited FD operations. The order inwhich the exemplary method is described is not intended to be construedas a limitation, and any number of the described blocks may be combinedin any order to implement the exemplary method disclosed herein, or anequivalent alternative method. Additionally, individual blocks may bedeleted from the exemplary method without departing from the spirit andscope of the subject matter described herein. For discussion purposes,the exemplary method is described with reference to the implementationsof FIGS. 1-2.

The exemplary method aims to simplify processes and computationsinvolved in monitoring and detection of a fall event corresponding to anobject such as the person 102 of FIG. 1 by using a 3D range camera asthe DAS. An advantage of employing the 3D range camera is the use ofnon-identifiable images for monitoring and detection of the fall eventinstead of the personally identifiable video images used by conventionalmonitoring systems that are grossly intrusive on personal space.Accordingly, the DAS, such as the DAS 104 of FIG. 1 is appropriatelypositioned to acquire data corresponding to relevant regions of thefield of view such as the field of view 106 of FIG. 1. In oneembodiment, the DAS is positioned approximately at the center of theceiling of a room to acquire image and range data associated with thepixels corresponding to the field of view such as the field of view 106of FIG. 1. In alternative embodiments, however, the DAS may bepositioned at other locations such as on one of the walls adjacent to astaircase or a stair well that allow for the field of view of the DAS toinclude regions where a risk associated with a potential fall event maybe high.

Particularly, at step 302, the processing subsystem generates an initialrange image corresponding to the field of view of the DAS. The initialrange image is based on a relative distance of the pixels correspondingto one or more objects disposed in the field of view from a referencepoint such as the DAS. Accordingly, in one embodiment, the DAS emitspulses of infra-red (IR) light towards the field of view and detects thelight reflected from a surface of the one or more objects disposed inthe field of view. Further, the processing subsystem determines adistance based on a time taken by the emitted pulses to travel from theDAS to the one or more objects disposed in the field of view and back tothe DAS. Moreover, the energy corresponding to the light reflected fromthe pixels corresponding to the one or more objects correlates inverselyto the distance of the one or more objects from the DAS. The processingsubsystem, therefore, determines the distance of the one or more objectsfrom the DAS based on the detected energy of the pixel, the determinedtime taken by the pulses and the knowledge of the speed of light. Inalternative embodiments, where the DAS is positioned on a wall of theroom, standard trigonometric functions may be used to appropriatelymodify the distance computations. Particularly, the distancecomputations may be modified for reconciling an angular positioning ofthe DAS and/or calculating relative distances from another referencepoint.

Further, the processing subsystem arranges the one or more objects in aplurality of layers in the initial range image according to thecorresponding distance information determined by the processingsubsystem. The layered arrangement allows quick determination of acurrent position of the one or more objects in the field of view inrelation to the other objects in the field of view in near real timewhile using minimal processing power. Moreover, the initial range imageprovides a baseline configuration of the field of view and the one ormore objects disposed in the field of view that may be representative ofa default or low-risk configuration. As previously noted, the one ormore objects identified from the initial range image may be masked asbeing representative of safe regions having low fall risk.

Subsequently, at step 304, a reference plane such as the reference plane110 of FIG. 1 is identified in the initial range image. As previouslynoted, the reference plane may correspond to a floor of a room, a bed ora chair disposed in the room or any other suitable plane in the field ofview. The reference plane is identified using a processing subsystemsuch as the processing subsystem 112 of FIG. 1 that is operativelycoupled to the DAS through a wired and/or wireless communication linksuch as the communication network 202 of FIG. 2.

In one embodiment, the processing subsystem designates a group of pixelsoriented as a plane disposed furthest from the DAS on an axissubstantially perpendicular to the DAS as the reference plane. Inanother embodiment, the processing subsystem employs an exemplaryheuristic to select the largest cluster disposed at the furthestdistance from the DAS as the reference plane. Alternatively, a group ofpixels oriented as a plane having the lowest Z coordinate position maybe identified as the reference plane. In certain other embodiments, aplane at a determined distance from the DAS may be designated to be thereference plane. Accordingly, the system may include, for example, aswitching mechanism to select a mounting height of the DAS to be set ata designated height such as 8, 10, or 12 feet from the reference planesuch as a floor in a room. Additionally, in embodiments where the DAS ismounted on a sidewall adjacent to a staircase or a stairwell, thereference plane may be derived to generate a relative reference plane,an angled reference plane, or a plurality of reference planes such as inrelation to a number of stairs.

Further, at step 306, the processing system determines one or moreregions in the initial range image indicative of one or more objectsdisposed above the reference plane. In certain embodiments, theprocessing subsystem further masks the one or more objects identifiedfrom the initial range image as being representative of safe regionswhere a risk associated with a potential fall event is low.

FIG. 4 illustrates an exemplary representation 400 of an initial rangeimage corresponding to the field of view of a DAS. Particularly, in FIG.4, elements 402 and 404 represent objects disposed above a referenceplane 406. By way of example, the element 402 may correspond to a smalltable whereas the element 404 may correspond to a person standingupright in the field of view. Further, an element 408 in the initialrange image indicates a determined height. By way of example, thedetermined height 408 corresponds to about 21 inches. The initial rangeimage 400 further includes an element 410 representative of a pluralityof grey scale values indicative of relative distances of pixelscorresponding to the field of view from the DAS.

As the corresponding height of the elements 402 and 404 is less than thedetermined height 408 and the corresponding surface area and/or volumeof elements 402 and 404 is less than a determined surface area and/or adetermined volume, elements 402 and 404 represent objects disposed inlow-risk positions in the field of view. The configuration of the fieldof view depicted in FIG. 4, therefore, triggers no alerts to appropriatepersonnel or an associated health monitoring system. Further, theinitial range image depicted in FIG. 4 provides a baseline configurationof the field of view and the one or more objects represented by theelements 402 and 404 disposed in the field of view representative of adefault or low-risk configuration.

Referring again to FIG. 3, at step 308, the processing subsystem directsthe DAS to continually regenerate a range image corresponding to thefield of view after a determined time period, for example, after every 3seconds. Subsequently, the processing subsystem, at step 310, comparesthe regenerated range image with the initial range image for determiningif the regenerated range image includes a new object disposed above thereference plane 406 in the field of view. Specifically, the processingsubsystem determines if the regenerated range image includes a newsurface disposed above the reference plane 406 in addition to theinitially identified objects present in the initial range imagecorresponding to the field of view. Upon identifying the new surface,the processing subsystem designates the new surface to be representativeof the new object disposed above the reference plane 406.

Further, the processing subsystem determines a height and a surface areaand/or a volume of the new object. As previously noted, the processingsubsystem determines the height of the new object based on a distance ofthe highest pixel corresponding to the new object from the referenceplane. Additionally, the processing subsystem may determine the surfacearea of the new object by summing an approximate size of each of thepixels determined by using standard trigonometric functions. Moreover,the processing subsystem may determine the volume of the new object bysumming the volume of space above the reference plane represented byeach individual pixel corresponding to the new object.

In accordance with aspects of the present technique, at step 312, theprocessing subsystem determines if the height of the new object is lessthat a determined height and the surface area and/or the volume of thenew object is greater than a determined value. In one embodiment, thedetermined height corresponds to a height such that a substantialportion of high-risk movements such as the person crawling into the roomor twitching on the floor may be confined below the determined height.In another embodiment, the determined height corresponds to a waistheight of the person, such as about 21 inches above the reference plane.

Generally, the processing subsystem designates a height as thedetermined height to minimize false alarms by ensuring that at least aportion of the low-risk movements corresponding to the person lying on abed or sitting in a chair disposed in the field of view is detectedabove the determined height. Alternatively, the determined height may bebased on application requirements, such as size of the object to bemonitored, a relative distance of the new object in the field of viewand/or a resolution and range corresponding to the DAS.

In one embodiment, the processing subsystem designates a surface area,for example about 3 ft², corresponding to a surface area of an averageperson disposed in a low-risk position such as while standing or sittingin the field of view as the determined surface area. Typically, asurface area greater than the determined surface area is indicative ofthe person who may have fallen and is disposed on the floor.

Similarly, the processing subsystem designates a volume, for exampleabout 18,000 cm³, corresponding to a volume of an average person whilestanding or sitting in the field of view as the determined volume.Typically, a volume greater than the determined volume is indicative ofthe person who may have fallen and is disposed on the floor. In certaincases, however, such as when a person stands with outstretched arms anda volume computation includes volume of the pixels corresponding to thetop of the arm to the reference plane, the volume of the person may begreater than the determined volume.

Therefore, the processing subsystem designates the new object to be thefallen person only if the height of the new object is less than thedetermined height and the surface area and/or the volume of the newobject is greater than the determined value. Particularly, theprocessing subsystem designates the new object to be the fallen personif the values corresponding to the determined height and the determinedsurface area and/or the determined volume do not change over adetermined period of time. As previously noted, the determined period oftime corresponds to a recovery time during which the person may get upsubsequent to a fall. By way of example, the determined period of timemay be about 90 seconds. The processing subsystem, however, may vary thedetermined period of time based on other parameters such as a locationof the fall and/or the presence of another person in the field of view.

Further, at step 314, the processing subsystem generates an outputthrough an output device coupled to the DAS and/or the processingsubsystem if the height of the new object is less than the determinedheight and the surface area and/or the volume of the new object isgreater than the determined value.

The generated output may include an audio output and/or a visual outputsuch as flashing lights, display messages and/or an alarm through analarm unit, an audio transmitter, a video transmitter, a display unit,or combinations thereof. Additionally, the generated output may becommunicated as an alert signal through a wired and/or wireless link toappropriate personnel and/or another monitoring system to generate awarning and/or obtain assistance for the fallen person. An exemplaryrepresentation of a regenerated range image used to detect a new objectdisposed above the reference plane in a field of view and generate analert upon determining a potential fall event corresponding to the newobject is depicted in FIG. 5.

FIG. 5 illustrates an exemplary representation 500 of a regeneratedrange image corresponding to the field of view illustrated in FIG. 4.Particularly, in FIG. 5, the elements 402 and 404 represent objectsdisposed above the reference plane 406. As previously noted, the element402 corresponds to a small table. The element 404 according to thedepictions of FIG. 5, however, corresponds to a person who may haveexperienced a fall event and is disposed above the reference plane 406in the field of view. Moreover, the element 408 in the regenerated rangeimage indicates the determined height. As the height of the element 404is less than the determined height 408 and the surface area and/or thevolume of the element 404 is more than the determined value, theprocessing subsystem determines the element 404 to be representative ofa person having experienced a potential fall event. The processingsubsystem, therefore, triggers an alert to an appropriate personnel oran associated health monitoring system for obtaining the requiredassistance for the fallen person.

The FD system and method disclosed hereinabove, thus, employs simple yetrobust computations for monitoring and detecting fall events.Specifically, the system allows detection of a fall event simply bydetermining the height, the surface area and/or the volume of an objectdisposed in the field of view. The determination of the height, thesurface area and/or the volume of the new object is greatly facilitatedby the use of a range-imaging device as the DAS. Further, therange-imaging device generates a range image of the entire field of viewsimultaneously as opposed to reading one pixel or line at a time as inconventional FD applications. The use of the range-imaging device as theDAS, therefore, enables faster computations while using minimalprocessing. Accordingly, standard-processing devices may be used forperforming computations relevant to monitoring the field of view,thereby reducing equipment cost and complexity.

Moreover, the range imaging device uses a depth map of the field of viewas opposed to using an entire image to detect the fallen person used inconventional video-based monitoring applications. As previously noted,the depth map includes a plurality of range values representative of arelative distance of each object disposed in the field of view.Employing the depth map, thus, eliminates the need to store imagesand/or other personally identifiable information, thereby mitigatingprivacy concerns.

Although the exemplary embodiments of the present system disclose theuse of a 3D range camera, use of any other suitable type of rangeimaging device, such as an active infrared and/or a time-of-flightdevice for detecting a fallen object is also contemplated.

While only certain features of the present invention have beenillustrated and described herein, many modifications and changes willoccur to those skilled in the art. It is, therefore, to be understoodthat the appended claims are intended to cover all such modificationsand changes as fall within the true spirit of the invention.

The invention claimed is:
 1. A method for detecting a fallen person,comprising: generating an initial range image corresponding to a fieldof view of a data acquisition system; identifying a reference planedisposed in the field of view of the data acquisition system;determining one or more regions in the initial range image indicative ofone or more objects disposed above the reference plane in the field ofview of the data acquisition system; regenerating a range imagecorresponding to the field of view of the data acquisition system aftera determined time period; comparing the regenerated range image with theinitial range image to determine if the regenerated range imagecomprises a new object disposed above the reference plane; anddetermining whether the new object disposed above the reference plane isthe fallen person if a height of the new object is less than adetermined height and at least one of a volume and a surface area of thenew object is greater than a determined value.
 2. The method of claim 1,wherein generating the range image corresponding to the field of view ofthe data acquisition system comprises generating a plurality of rangevalues indicative of relative distances of one or more objects disposedin the field of view.
 3. The method of claim 1, wherein identifying thereference plane disposed in the field of view comprises identifying agroup of pixels oriented as a plane disposed furthest from the dataacquisition system or a plane disposed at a determined distance from thedata acquisition system.
 4. The method of claim 1, wherein determiningthe one or more regions in the initial range image indicative of one ormore objects disposed above the reference plane in the field of view ofthe data acquisition system comprises masking the one or more objects inthe initial range image.
 5. The method of claim 1, wherein regeneratingthe range image corresponding to the field of view of the dataacquisition system comprises continually regenerating the range imagecorresponding to the field of view of the data acquisition system afterthe determined time period.
 6. The method of claim 1, wherein comparingthe regenerated range image with the initial range image furthercomprises determining a duration of a movement of the one or moreobjects, the new object, or a combination thereof, in the determinedtime period.
 7. The method of claim 1, wherein determining whether thenew object disposed above the reference plane is the fallen personcomprises designating a desired height as the determined height and atleast one of a desired surface area and a desired volume as thedetermined value.
 8. The method of claim 1, further comprisinggenerating an output upon determining that the fallen person is disposedabove the reference plane for more than a determined duration of time.9. The method of claim 8, wherein generating the output comprisesgenerating an audio output, a visual output, an alert message, or acombination thereof.
 10. A system for detecting a fallen person,comprising: a data acquisition system that generates an initial rangeimage corresponding to a field of view of the data acquisition system;and a processing subsystem, communicatively coupled to the dataacquisition system, wherein the processing subsystem: identifies areference plane disposed in the field of view of the data acquisitionsystem; determines one or more regions in the initial range imageindicative of one or more objects disposed above the reference plane inthe field of view of the data acquisition system; regenerates a rangeimage corresponding to the field of view of the data acquisition systemafter a determined time period; compares the regenerated range imagewith the initial range image to determine if the regenerated range imagecomprises a new object disposed above the reference plane; anddetermines whether the new object disposed above the reference plane isthe fallen person if a height of the new object is less than adetermined height and at least one of a volume and a surface area of thenew object is greater than a determined value.
 11. The system of claim10, wherein the data acquisition system comprises a range imaging devicethat uses the time-of-flight, coded aperture, structured light, or thetriangulation principle.
 12. The system of claim 10, wherein the dataacquisition system generates the initial range image corresponding tothe field of view of the data acquisition system by generating aplurality of grey scale or color scale values indicative of a relativedistance of the one or more objects disposed in the field of view. 13.The system of claim 10, wherein the processing subsystem directs thedata acquisition system to continually regenerate the range imagecorresponding to the field of view of the data acquisition system afterthe determined time period.
 14. The system of claim 10, wherein theprocessing subsystem further determines a duration of a movement of theone or more objects, the new object, or a combination thereof, in thedetermined time period.
 15. The system of claim 14, further comprisingtiming circuitry communicatively coupled to the processing subsystemthrough a wired network, a wireless network, or a combination thereof,for determining the determined time period corresponding to theregeneration of the range image and the determined duration of movement.16. The system of claim 10, further comprising an output unit thatgenerates an output upon determining the fallen object is disposed onthe floor for more than a determined duration of time, wherein theoutput unit is communicatively coupled to the processing subsystemthrough a wired network, a wireless network, or a combination thereof.17. The system of claim 16, wherein the output unit comprises an alarmunit, an audio transmitter, a video transmitter, a display unit, orcombinations thereof.